Machine learningDeep learning / NLP / CV

Semantička segmentacija

Semantička segmentacija dodjeljuje oznaku klase svakom pikselu u slici, stvarajući gustu kartu scene s anotacijama kategorija. Za razliku od detekcije objekata, koja crta pravokutne okvire, ona razgraničava točan prostorni opseg svake klase, što je čini neophodnom u medicinskom snimanju, autonomnoj vožnji, satelitskoj analizi i bilo kojem zadatku gdje su precizne granice regija važne.

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Izvori

  1. Long, J., Shelhamer, E., & Darrell, T. (2015). Fully convolutional networks for semantic segmentation. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 3431–3440. DOI: 10.1109/CVPR.2015.7298965
  2. Chen, L.-C., Papandreou, G., Kokkinos, I., Murphy, K., & Yuille, A. L. (2018). DeepLab: Semantic image segmentation with deep convolutional nets, atrous convolution, and fully connected CRFs. IEEE Transactions on Pattern Analysis and Machine Intelligence, 40(4), 834–848. DOI: 10.1109/TPAMI.2017.2699184

Kako citirati ovu stranicu

ScholarGate. (2026, June 3). Semantic Segmentation (Dense Pixel-wise Classification). ScholarGate. https://scholargate.app/hr/deep-learning/semantic-segmentation

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ScholarGateSemantic Segmentation (Semantic Segmentation (Dense Pixel-wise Classification)). Preuzeto 2026-06-15 s https://scholargate.app/hr/deep-learning/semantic-segmentation · Skup podataka: https://doi.org/10.5281/zenodo.20539026